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1.
Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations
to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the
effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to
the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other
hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the
time series analysed, due to their strong masking effects.
Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations
observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic
density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and
climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February
2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied.
One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong
persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons
is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological
variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial
dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter.
The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O3 and PM to examine underlying trends.
Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model
yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval
for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in
trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates
out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results
in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal
variations.
Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the
analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological
conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions.
There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle
and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic
density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions
which is a direct consequence of the holiday period.
Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend
results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect
of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering
the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an
estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions.
Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant
reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site
with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes
in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability 相似文献
2.
基于日本GOSAT及美国AIRS反演数据产品,对我国中部六省大气CO2时空分布特征进行研究,结果表明:由GOSAT反演的中部地区2010~2013年大气CO2年均柱浓度由389.36×10-6增长到396.52×10-6,年均绝对增长率达2.39×10-6/a,呈现出冬春季高值、夏秋季低值的季节变化特征,其柱浓度年均值及去长期趋势后的月均值均略低于长三角地区,高于京津冀和东三省地区;其CO2柱浓度高值区集中在湖南、江西及周边一带,年均绝对增长率为2.01×10-6,其柱浓度年均值及去长期趋势后的月均值与长三角地区相当,略低于京津冀和东三省地区,由于受地面源汇影响较小,其与GOSAT反演结果相反,可能是由于AIRS反映了对流层中层大气状况,而GOSAT则更多地反映了近地面层大气CO2变化. 相似文献
3.
乌鲁木齐市汽车尾气污染状况调查 总被引:1,自引:0,他引:1
对乌鲁木齐市主要街道受汽车尾气污染的调查和综合分析得到CO、NOx、HC的污染规律,主要街道路中心空气中CO、NOx日均值已超出国家大气环境质量二级标准,市区主要街道的人行道空气中NOx含量已超出二级标准,Ⅱ、Ⅲ类道路人行道空气中CO含量已超标;在三类街道中,Ⅰ类街道车流量最大,Ⅱ类次之,Ⅲ类最少,而汽车排放尾气对街道空气污染状况为Ⅲ类最重、Ⅱ类次之、Ⅰ类最轻。 相似文献
4.
关于我国一氧化碳室内空气质量评价标准的建议 总被引:1,自引:0,他引:1
人们大部分时间处于室内,室内空气质量直接影响人们的身体健康。当前,室内空气污染己成为社会关注的热点问题,一氧化碳(CO)含量高低是室内空气质量(IAQ)好坏的重要指示指标。本文通过分析一氧化碳(CO)的理化特性,来源,毒理学研究和流行病学研究结果,在参考世界卫生组织(WHO)或国外相关标准的基础上,结合我国的实际情况和目前污染水平,首次提出了我国一氧化碳(CO)室内空气质量三级标准建议值。 相似文献
5.
6.
常温下考察了焙烧温度、金含量及水分对Au/ZnO催化剂上CO氧化性能的影响 ,并在常湿条件下考察了ZnO上CO氧化活性同温度的关系。结果表明 ,金的存在极大地提高了催化剂CO的氧化活性。另外焙烧温度和金含量对Au/ZnO催化剂的活性和稳定性均有较大影响 ,在常温常湿条件下 ,2 4 0℃焙烧的 2 %Au/ZnO催化剂 ,可连续反应 1 750h保持CO完全转化。XRD结果表明 ,锌的化学状态对催化剂的稳定性有较大的影响 ,氧化锌较碳酸锌表现出较高的稳定性。 相似文献
7.
介绍了造成中国石化齐鲁分公司硫黄回收装置烟气CO排放浓度高的原因,并制定了相应的改造方案。对装置目前可实施的运行参数进行了优化调整,个别装置CO排放可达100 mg/m 3以下,其他装置等待检修时改造实施。 相似文献
8.
9.
10.
通过沉淀和溶解两方面的实验数据,应用PHREEQC程序模拟了砷酸钙在不同CO2分压条件下溶解度的变化情况,发现环境中的CO2可使砷酸钙盐在酸度较高(pH大于8.3)的条件下发生不一致溶解,使其溶解度升高;CO2分压越大,砷酸钙盐发生不一致溶解的酸度越低;CO2主要影响3∶2和5∶3的砷酸钙盐,而对4∶2砷酸钙盐的影响较小。这对不同类型砷酸钙盐废物的处置是否应考虑CO2的因素提供了依据。 相似文献